During recent IBM analyst big data event, I learned about a new product, IBM Predictive Customer Intelligence. It extracts and processes customer-related data from multiple sources to analyze customer-related activities and has capabilities to predict customer behavior and actions. Predictive Customer Intelligence is built on IBM’s big data platform and supports extraction and integration of data from multiple sources, internal and external, and from structured and unstructured data. It can process data created by third-party products, such as text-based files of data created by converting speech to text. The product can capture and analyze customer interactions from multiple communication channels such as voice, email, text messages, chat and Web usage scripts and social media posts.
Topics: Social Media, Customer Analytics, Customer Experience, Voice of the Customer, IBM Predictive Customer Intelligence, Analytics, Business Analytics, Business Intelligence, Cloud Computing, Collaboration, Customer & Contact Center, Customer Service, IBM, Information Applications, Call Center, Contact Center, Contact Center Analytics, IBM Watson, Text Analytics
The contact center market continues to shift focus from handling customer calls as efficiently as possible to providing superior customer engagement across multiple touch points. The latest advancement is an joint announcement from IBM and Genesys who have signed a partnership agreement to provide “smarter customer engagement”. The agreement includes a technology partnership and a joint marketing plan, and brings together IBM’s Watson Engagement Advisor and Genesys’ Customer Experience Platform.
Topics: Social Media, Customer Experience, Genesys, Mobile Apps, Self-service, Operational Performance, Cloud Computing, Customer & Contact Center, Customer Service, Call Center, Cognitive Computing, Contact Center, CRM, IBM Watson
At its recent Connect 2014 event IBM announced IBM Kenexa Talent Suite, an integrated talent management suite. The release strengthens its Smarter Workforce initiative by combining IBM and Kenexa products and services in one human capital management (HCM) offering. IBM Kenexa Talent Suite also addresses increasing efforts by human resources organizations to optimize their activities through more effective use of technology, a topic covered in our 2014 HCM research agenda. Specifically, the release integrates talent management process automation capabilities with collaboration and also can be complemented with its workforce analytics to help organizations be more efficient and productive; our benchmark research shows these are the leading benefits of using human capital analytics systems.
Topics: Big Data, Mobile, SAP, Social Media, HCM, Kenexa, Recruiting, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Cloud Computing, Collaboration, IBM, Oracle, Workforce Performance, Cognitive Computing, HR, IBM Watson, Social
With much fanfare and a rarely seen introduction by CEO Ginni Rometty, IBM launched IBM Watson as a new business unit focused on cognitive computing technology and solutions, now being led by Senior Vice President Mike Rhodin. The announcement is summarized here:. Until now IBM Watson was important but had neither this stature in IBM’s organizational structure nor enough investment to support what the company proclaims is the third phase of computing. As IBM tells it, computing paradigms began with the century-old tabular computing, followed by the age of programmatic computing, in which IBM developed many products and advancements. The third phase is cognitive computing, an area in which the company has invested significantly to advance its technology. IBM has been on this journey for some time, long before the IBM Watson system beat humans on Jeopardy!. Its machine-learning efforts started with the IBM 704 and computer checkers in the 1950s, followed by decades of utilizing the computing power of the IBM 360 mainframe, the IBM AS/400, the IBM RS/6000 and even IBM XT computers in the 1980s. Now IBM Watson is focused on reaching the full potential of cognitive computing.
Topics: Big Data, Sales Performance, Social Media, Supply Chain Performance, IT Performance, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Performance, CIO, Cloud Computing, Customer & Contact Center, Financial Performance, Governance, Risk & Compliance (GRC), Information Applications, Information Management, Location Intelligence, Operational Intelligence, Workforce Performance, Cognitive Computing, Discovery, Exploration, IBM Watson
I recently wrote how IBM is making customer analytics smarter. Since then IBM has run events in North America and Europe to demonstrate how it is continuing these efforts and expanding into other areas. Outside of the customer space you can read how my colleagues assess its efforts: Mark Smith discusses HR, Robert Kugel sees its impact on business overall, and Tony Cosentino addresses it in IT. Our research My focus remains the customer and I have learned more about what IBM is doing in social media, identity reconciliation, visualization, mobile apps and big data.
Topics: Social Media, Customer Analytics, Customer Experience, Speech Analytics, Voice of the Customer, Mobile Apps, Self-service, Analytics, Business Analytics, Business Collaboration, Cloud Computing, Collaboration, Customer & Contact Center, Customer Service, IBM, Call Center, Contact Center, Contact Center Analytics, CRM, Desktop Analytics, IBM Watson, Text Analytics